The quality and safety of food is an important issue to the whole society, since it is at the basis of human health, social development and stability. Ensuring food quality and safety is a complex process, and all stages of food processing must be considered, from cultivating, harvesting and storage to preparation and consumption. However, these processes are often labour-intensive. Nowadays, the development of machine vision can greatly assist researchers and industries in improving the efficiency of food processing. As a result, machine vision has been widely used in all aspects of food processing. At the same time, image processing is an important component of machine vision. Image processing can take advantage of machine learning and deep learning models to effectively identify the type and quality of food. Subsequently, follow-up design in the machine vision system can address tasks such as food grading, detecting locations of defective spots or foreign objects, and removing impurities. In this paper, we provide an overview on the traditional machine learning and deep learning methods, as well as the machine vision techniques that can be applied to the field of food processing. We present the current approaches and challenges, and the future trends.

Sulfolane is a groundwater pollutant. While sulfolane is miscible in pure water, its miscibility in the presence of ions has not been widely investigated. This aspect is relevant to predict sulfolane migration in groundwater. Na2SO4 separates sulfolane from water, yielding bulk separation, emulsions seen by optical microscopy or molecular sulfolane clusters. We study these clusters with fluorescence spectroscopy, small-angle x ray (SAXS) and neutron (SANS) scattering, and x-ray absorption fine structure (XAFS). Fluorescence spectroscopy reveals non-monotonic changes in the local viscosity of the water phase with 10% sulfolane and 0.25-1M Na2SO4, likely resulting from the interplay between sulfolane clustering and enhanced interactions between water molecules. NaCl affects the micro-viscosity of water similarly to Na2SO4, but at higher concentrations. At low sulfolane percentages, Cl− decreases the activity coefficients of water and sulfolane, suggesting stronger sulfolane–sulfolane and water–water interactions. SAXS confirms that Na2SO4 induces sulfolane clustering. SAXS data modeled with a power law and a Gaussian reveal a correlation length ξ = 16.3 Å, which we view as the radius of a sulfolane cluster surrounded by water and Na+ ions. SANS also shows that 2 mol. % of sulfate and chloride salts induce sulfolane clustering, with sulfates having a more marked effect. Furthermore, XAFS reveals that sulfates affect sulfolane sorption onto Si3N4 surfaces. Without Na2SO4, sulfolane directly sorbs onto Si3N4 surfaces. Conversely, with Na2SO4, water is directly sorbed onto Si3N4, likely because it surrounds sulfolane clusters. Also, hydrated Na+ ions are in Si3N4 surface proximity.

Tetrahydrofuran (THF) is fully miscible in water, and it interacts with it via hydrogen (H) bonds. We discover that the fatty acid hydroxystearic acid (HSA) separates THF from water because it preferentially H-bonds water and increases the proportion of single H-bond donors (SD) relative to double H-bond donors (DD). This change in the coordination of water molecules from DD to SD leads to phase separation between THF and water. We previously established this separation mechanism using sugars and surfactants and other water miscible solvents. Here, we use attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) to prove that this mechanism is also responsible for THF–water separation using HSA, thereby demonstrating the universality of the proposed separation mechanism. Using synchrotron small-angle x-ray scattering, we show how HSA self-assembles into reverse micelles in THF–water mixtures and determine their persistence length and periodicity using a modified Landau model. Reverse micelles host water in their interior and swell upon increasing the water content, as shown by light scattering. They then turn into droplets detectable using optical or confocal microscopy. When THF–water emulsions separate, they yield water-rich and THF-rich free phases. ATR-FTIR reveals that the top phase of THF–water mixtures separated by HSA is THF-rich. Moreover, when Cu²⁺ ions are in solution, HSA causes their migration into the THF-rich phase, enabling the simultaneous separation of THF and Cu²⁺ cations from water. This study demonstrates the potential for engineering the water structure to aid in the separation of water-miscible solvents from water with important implications for water treatment.